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mcsm_analysis/pyrazinamide/scripts/replaceBfactor_pdb.R
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386
mcsm_analysis/pyrazinamide/scripts/replaceBfactor_pdb.R
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getwd()
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setwd("~/git/LSHTM_analysis/mcsm_analysis/pyrazinamide/scripts")
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getwd()
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########################################################################
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# Installing and loading required packages #
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########################################################################
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source("Header_TT.R")
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#########################################################
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# TASK: replace B-factors in the pdb file with normalised values
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# use the complex file with no water as mCSM lig was
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# performed on this file. You can check it in the script: read_pdb file.
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#########################################################
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###########################
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# 2: Read file: average stability values
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# or mcsm_normalised file, output of step 4 mcsm pipeline
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###########################
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inDir = "~/git/Data/pyrazinamide/input/processed/"
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inFile = paste0(inDir, "mean_PS_Lig_Bfactor.csv"); inFile
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my_df <- read.csv(inFile
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# , row.names = 1
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# , stringsAsFactors = F
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, header = T)
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str(my_df)
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#=========================================================
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# Processing P1: Replacing B factor with mean ratioDUET scores
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#=========================================================
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#########################
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# Read complex pdb file
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# form the R script
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##########################
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source("read_pdb.R") # list of 8
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# extract atom list into a variable
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# since in the list this corresponds to data frame, variable will be a df
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d = my_pdb[[1]]
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# make a copy: required for downstream sanity checks
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d2 = d
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# sanity checks: B factor
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max(d$b); min(d$b)
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#*******************************************
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# plot histograms for inspection
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# 1: original B-factors
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# 2: original DUET Scores
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# 3: replaced B-factors with DUET Scores
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#*********************************************
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# Set the margin on all sides
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par(oma = c(3,2,3,0)
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, mar = c(1,3,5,2)
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, mfrow = c(3,2))
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#par(mfrow = c(3,2))
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#1: Original B-factor
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hist(d$b
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, xlab = ""
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, main = "B-factor")
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plot(density(d$b)
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, xlab = ""
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, main = "B-factor")
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# 2: DUET scores
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hist(my_df$average_DUETR
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, xlab = ""
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, main = "Norm_DUET")
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plot(density(my_df$average_DUETR)
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, xlab = ""
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, main = "Norm_DUET")
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# 3: After the following replacement
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#********************************
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#=========
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# step 0_P1: DONT RUN once you have double checked the matched output
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#=========
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# sanity check: match and assign to a separate column to double check
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# colnames(my_df)
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# d$ratioDUET = my_df$averge_DUETR[match(d$resno, my_df$Position)]
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#=========
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# step 1_P1
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#=========
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# Be brave and replace in place now (don't run sanity check)
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# this makes all the B-factor values in the non-matched positions as NA
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d$b = my_df$average_DUETR[match(d$resno, my_df$Position)]
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#=========
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# step 2_P1
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#=========
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# count NA in Bfactor
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b_na = sum(is.na(d$b)) ; b_na
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# count number of 0's in Bactor
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sum(d$b == 0)
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#table(d$b)
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# replace all NA in b factor with 0
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d$b[is.na(d$b)] = 0
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# sanity check: should be 0
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sum(is.na(d$b))
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# sanity check: should be True
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if (sum(d$b == 0) == b_na){
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print ("Sanity check passed: NA's replaced with 0's successfully")
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} else {
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print("Error: NA replacement NOT successful, Debug code!")
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}
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max(d$b); min(d$b)
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# sanity checks: should be True
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if(max(d$b) == max(my_df$average_DUETR)){
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print("Sanity check passed: B-factors replaced correctly")
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} else {
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print ("Error: Debug code please")
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}
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if (min(d$b) == min(my_df$average_DUETR)){
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print("Sanity check passed: B-factors replaced correctly")
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} else {
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print ("Error: Debug code please")
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}
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#=========
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# step 3_P1
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#=========
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# sanity check: dim should be same before reassignment
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# should be TRUE
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dim(d) == dim(d2)
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#=========
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# step 4_P1
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#=========
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# assign it back to the pdb file
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my_pdb[[1]] = d
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max(d$b); min(d$b)
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#=========
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# step 5_P1
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#=========
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# output dir
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getwd()
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outDir = "~/git/Data/pyrazinamide/input/structure/"
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outFile = paste0(outDir, "complex1_BwithNormDUET.pdb"); outFile
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write.pdb(my_pdb, outFile)
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#********************************
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# Add the 3rd histogram and density plots for comparisons
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#********************************
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# Plots continued...
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# 3: hist and density of replaced B-factors with DUET Scores
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hist(d$b
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, xlab = ""
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, main = "repalced-B")
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plot(density(d$b)
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, xlab = ""
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, main = "replaced-B")
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# graph titles
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mtext(text = "Frequency"
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, side = 2
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, line = 0
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, outer = TRUE)
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mtext(text = "DUET_stability"
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, side = 3
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, line = 0
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, outer = TRUE)
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#********************************
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#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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# NOTE: This replaced B-factor distribution has the same
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# x-axis as the PredAff normalised values, but the distribution
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# is affected since 0 is overinflated. This is because all the positions
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# where there are no SNPs have been assigned 0.
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#!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
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#######################################################################
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#====================== end of section 1 ==============================
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#######################################################################
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#=========================================================
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# Processing P2: Replacing B values with PredAff Scores
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#=========================================================
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# clear workspace
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rm(list = ls())
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###########################
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# 2: Read file: average stability values
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# or mcsm_normalised file, output of step 4 mcsm pipeline
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###########################
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inDir = "~/git/Data/pyrazinamide/input/processed/"
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inFile = paste0(inDir, "mean_PS_Lig_Bfactor.csv"); inFile
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my_df <- read.csv(inFile
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# , row.names = 1
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# , stringsAsFactors = F
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, header = T)
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str(my_df)
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#rm(inDir, inFile)
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#########################
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# 3: Read complex pdb file
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# form the R script
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##########################
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source("read_pdb.R") # list of 8
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# extract atom list into a variable
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# since in the list this corresponds to data frame, variable will be a df
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d = my_pdb[[1]]
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# make a copy: required for downstream sanity checks
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d2 = d
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# sanity checks: B factor
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max(d$b); min(d$b)
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#*******************************************
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# plot histograms for inspection
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# 1: original B-factors
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# 2: original Pred Aff Scores
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# 3: replaced B-factors with PredAff Scores
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#********************************************
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# Set the margin on all sides
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par(oma = c(3,2,3,0)
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, mar = c(1,3,5,2)
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, mfrow = c(3,2))
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#par(mfrow = c(3,2))
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# 1: Original B-factor
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hist(d$b
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, xlab = ""
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, main = "B-factor")
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plot(density(d$b)
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, xlab = ""
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, main = "B-factor")
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# 2: Pred Aff scores
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hist(my_df$average_PredAffR
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, xlab = ""
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, main = "Norm_lig_average")
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plot(density(my_df$average_PredAffR)
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, xlab = ""
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, main = "Norm_lig_average")
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# 3: After the following replacement
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#********************************
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#=================================================
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# Processing P2: Replacing B values with ratioPredAff scores
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#=================================================
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# use match to perform this replacement linking with "position no"
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# in the pdb file, this corresponds to column "resno"
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# in my_df, this corresponds to column "Position"
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#=========
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# step 0_P2: DONT RUN once you have double checked the matched output
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#=========
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# sanity check: match and assign to a separate column to double check
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# colnames(my_df)
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# d$ratioPredAff = my_df$average_PredAffR[match(d$resno, my_df$Position)] #1384, 17
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#=========
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# step 1_P2: BE BRAVE and replace in place now (don't run step 0)
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#=========
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# this makes all the B-factor values in the non-matched positions as NA
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d$b = my_df$average_PredAffR[match(d$resno, my_df$Position)]
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#=========
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# step 2_P2
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#=========
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# count NA in Bfactor
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b_na = sum(is.na(d$b)) ; b_na
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# count number of 0's in Bactor
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sum(d$b == 0)
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#table(d$b)
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# replace all NA in b factor with 0
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d$b[is.na(d$b)] = 0
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# sanity check: should be 0
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sum(is.na(d$b))
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if (sum(d$b == 0) == b_na){
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print ("Sanity check passed: NA's replaced with 0's successfully")
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} else {
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print("Error: NA replacement NOT successful, Debug code!")
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}
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max(d$b); min(d$b)
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# sanity checks: should be True
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if (max(d$b) == max(my_df$average_PredAffR)){
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print("Sanity check passed: B-factors replaced correctly")
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} else {
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print ("Error: Debug code please")
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}
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if (min(d$b) == min(my_df$average_PredAffR)){
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print("Sanity check passed: B-factors replaced correctly")
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} else {
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print ("Error: Debug code please")
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}
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#=========
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# step 3_P2
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#=========
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# sanity check: dim should be same before reassignment
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# should be TRUE
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dim(d) == dim(d2)
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#=========
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# step 4_P2
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#=========
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# assign it back to the pdb file
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my_pdb[[1]] = d
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max(d$b); min(d$b)
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#=========
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# step 5_P2
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#=========
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# output dir
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outDir = "~/git/Data/pyrazinamide/input/structure/"
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outFile = paste0(outDir, "complex1_BwithNormLIG.pdb"); outFile
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write.pdb(my_pdb, outFile)
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#********************************
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# Add the 3rd histogram and density plots for comparisons
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#********************************
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# Plots continued...
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# 3: hist and density of replaced B-factors with PredAff Scores
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hist(d$b
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, xlab = ""
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, main = "repalced-B")
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plot(density(d$b)
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, xlab = ""
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, main = "replaced-B")
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# graph titles
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mtext(text = "Frequency"
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, side = 2
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, line = 0
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, outer = TRUE)
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mtext(text = "Lig_stability"
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, side = 3
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, line = 0
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, outer = TRUE)
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#********************************
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###########
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# end of output files with Bfactors
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##########
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